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areas. These include, but are not limited to: Applying machine learning algorithms to solve real-world problems. Creating and structuring databases for storage, retrieval, and image analysis. Determining
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improving plant health using machine learning and artificial intelligence. Mentor(s): The mentor for this opportunity is Yulin Jia (yulin.jia@usda.gov ). If you have questions about the nature of the research
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and weaknesses for end-users. Help develop new or improve existing soil moisture estimates using NISAR and other datasets utilizing artificial intelligence (AI) and machine learning. The outcome from
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& Amputation Center of Excellence (EACE) is a unique organization within the Department of War (DoW) consisting of teams of researchers embedded at the point of care within multiple Military Treatment Facilities
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Organization DEVCOM Army Research Laboratory Reference Code ARL-C-CISD-300144 Description About the Research Current approaches optimize machine learning training largely by exploiting Deep Neural
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learn how phenotypic datasets are integrated with genomic data for association analyses, genomic selection, and AI-driven methods, including machine learning and deep learning, to enhance germplasm
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collection of streaming sensor data. This project focuses on utilizing state-of-the-art reinforcement algorithms to 1) dynamically learn from multi-agent actions and context, 2) evaluate the environment and
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and Amputation Center of Excellence (EACE) is offering a postgraduate fellowship at the Uniformed Services University of the Health Sciences (USUHS) and Walter Reed National Military Medical Center
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ecosystem services that they provide. Learning Objectives: The participant will learn to utilize ecological simulation models and to design and conduct geospatial analysis of model results to characterize
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are offered an opportunity for an independent research project using lab data to gain experience conducting ecological data analysis, manuscript writing, and publishing in peer-reviewed journals. Learning